24results about How to "Easy parameter setting" patented technology

The invention relates to the technical field of remote control of mold temperature controllers, and discloses a remote temperature control method based on a mold temperature controller, which comprises the following steps: S1, collecting real-time temperature data of the mold temperature controller through a temperature sensor, and transmitting the data to a control system; s2, in a control system, performing real-time analysis and prediction on the acquired temperature data by using an intelligent algorithm and a machine learning model, and generating an adjustment instruction; s3, the adjusting instruction is sent to the mold temperature controller, and heating and cooling parameters of the mold temperature controller are adjusted in real time; and S4, connecting the mold temperature controller and the control system to an Internet of Things (IoT) platform to realize data intercommunication and cooperative control between the mold temperature controller and other production equipment. Temperature data are analyzed and predicted in real time through an intelligent algorithm and a machine learning model, an adjusting instruction is generated, heating and cooling parameters of the mold temperature controller are rapidly adjusted, and high-precision temperature control is achieved.

The invention relates to the field of mechanical engineering, and discloses a tentering setting production speed intelligent adjusting method and system, and the method comprises the steps: analyzing the thermal sensitivity, melting point, elastic coefficient and elastic modulus of a to-be-tentered textile; a heat setting curve of the to-be-tentered textile is constructed, the optimal setting temperature of the to-be-tentered textile is determined, and a heat setting control mechanism of the tentering setting machine is constructed; the stretching tension and the tentering tension of the to-be-tentered textile are calculated, the distance between spreading rollers and the speed of the spreading rollers of the tentering setting machine are analyzed, the cooling efficiency of the tentered textile is calculated, and a cooling control mechanism of the tentering setting machine is constructed; constructing a double-air-duct frequency conversion control module of the tentering setting machine; the tentering parameters of the tentering technological process are analyzed, the tentering state of the to-be-tentered textile in the tentering technological process is analyzed, the production speed parameters of the tentering setting machine are determined, and the production speed of the tentering setting machine is executed for intelligent adjustment. According to the invention, the production efficiency of tentering and shaping can be improved.

The invention relates to the technical field of signal detection, and discloses an unmanned aerial vehicle detection method, device and equipment based on a 5G network and a storage medium, the method is executed by a DAF responsible for data processing in an unmanned aerial vehicle detection system, the system further comprises an access and mobility management function AMF, and the method comprises the steps of receiving target sensor data corresponding to a target area, the target sensor data comprises a target RF signal and target image data corresponding to the target RF signal, processing the target RF signal through a random forest model to obtain a first recognition result, processing the target image data through an image recognition model to obtain a second recognition result, and outputting the second recognition result. And when both the first identification result and the second identification result indicate that the unmanned aerial vehicle exists in the target area, sending warning information to a third-party platform. According to the method, the random forest is combined with the image recognition model to perform anomaly analysis on the RF signal and the image data in the sensor data, so that high-precision real-time monitoring of the unmanned aerial vehicle is realized.

The invention belongs to the technical field of vehicle driving control, and particularly relates to an adaptive cruise safety self-evolution method, device and system based on a safety boundary. The method comprises the steps that vehicle driving data and environment information are collected and preprocessed, and a time sequence data set containing the state, control input and corresponding reward values of a vehicle in all time steps is obtained; secondly, dynamically evaluating the safety distance between the vehicle and surrounding obstacles through a control obstacle function, determining a safety area, and constructing and updating a safety driving boundary function of the vehicle at the same time; the MPC controller takes a safe driving boundary function as a constraint condition and takes a stable approaching target speed and a vehicle following distance as targets to obtain a control input sequence; and the vehicle executes corresponding operation according to the control parameters, and continuously adjusts the weight matrix of the MPC through an online optimization algorithm, so that the control parameters are gradually optimized. According to the method, adaptive adjustment of the MPC parameters is realized, so that the safety and the adaptive capacity of the vehicle in a complex traffic environment are improved.

The invention discloses an impedance measurement method, an implantable medical device and an implantable medical system. The impedance measurement method comprises the following steps: determining an expected interval of a current value applied to an electrode contact combination according to an electrode identifier of an electrode and the currently measured electrode contact combination; releasing measurement voltage to the electrode contact combinations and collecting current values between the electrode contact combinations; when the current value is not in the current value expected interval, adjusting the measurement voltage according to the current value; and when the current value is in a current value expected interval, determining an impedance value between the currently measured electrode contact combination according to the measured voltage and the current value. The accuracy of an impedance measurement result can be improved.

The invention discloses a hub motor fault diagnosis method and system based on SBAO improved RLMD, and belongs to the field of fault diagnosis based on sound vibration signals. The method and the device are used for solving the problems of low noise source identifiability, high cost and low fault diagnosis result accuracy caused by dependence on manual judgment in an existing motor fault diagnosis method based on sound and vibration signals. According to the invention, by designing the collection position and parameter setting of the sound and vibration sensor, a hub motor sound and vibration signal generated under an extreme condition can be captured; meanwhile, an optimized robustness local mean decomposition algorithm is adopted to process the acoustic vibration signals of the hub motor to obtain a feature set of an optimal IMF component of the acoustic vibration signals of the hub motor, and finally, the feature set is subjected to diagnosis result calculation through an enhanced random forest classifier, so that the accuracy of a fault diagnosis result is improved. According to the method, the efficiency and reliability of early fault diagnosis of the hub motor are improved, and powerful technical support is provided for subsequent optimization design of a hub motor structure.

The invention provides a relay protection device state evaluation system and method based on the Internet of Things, and relates to the technical field of the Internet of Things, and the method comprises the steps: obtaining the operation data of a relay protection device in real time through an Internet of Things communication system, the action record and the abnormal alarm information of the relay protection device are acquired; preprocessing the operation data of the relay protection device to obtain processed data; and according to the processed data, establishing an initial relay protection device state evaluation model, and training the relay protection device state evaluation model by using the processed data to obtain a final relay protection device state evaluation model. According to the invention, the data of the relay protection device is acquired and processed in real time through the Internet of Things, the evaluation model is established and trained, accurate evaluation of the state of the device is realized, and the stability and operation and maintenance efficiency of a power system are improved.

The invention discloses a chemical conveying control system, and relates to the technical field of special gas and chemical conveying, the system comprises the following components: a gas source: a high-pressure steel cylinder and a liquid storage tank are used as the gas source, the storage mode is selected according to the property of special gas chemicals, the high-pressure steel cylinder is made of seamless steel tubes, the sealing performance is good, the corrosion resistance is good, and the liquid storage tank is used for storing the special gas chemicals; the liquid storage tank can stably store liquid special gas chemicals for a long time and guarantee continuity of gas supply, the gas delivery control system adopts the high-pressure steel cylinder and the liquid storage tank as gas sources, and is combined with the high-strength corrosion-resistant pipeline and the valve control module (VMB), so that pollution and leakage of gas in the delivery process are reduced, and the gas delivery efficiency is improved. The high degree of finish of the inner surface of the pipeline and the specially designed joint ensure the purity of gas delivery, and the high requirements of the modern industry on special gas chemicals are met through accurate control of the PLC and real-time monitoring and adjustment of key parameters such as gas flow, pressure and temperature.

The invention provides a method for determining the content of phenolic organic matters in tar residue and phenolic wastewater, which comprises the following steps: optimizing an MRM (Magnetic Resonance Modeling) method based on a GC-QQQ optimizer to obtain an optimized MRM method; detecting mixed standard solutions of phenol, o-methylphenol and p-methylphenol with different concentration gradients by using an optimized MRM method to obtain a linear regression equation corresponding to the characteristic ion flow peak area and the concentration of each compound, and taking the linear regression equation as a quantitative standard curve equation of each compound; the method comprises the following steps: extracting organic matters in a liquid phase and a solid content of coal tar and phenolic wastewater raw materials into an organic phase, and circularly washing the raw materials for multiple times by using an extraction solvent to obtain a to-be-detected organic phase; detecting a to-be-detected organic phase by using an optimized MRM method, and comparing and matching the quantitative ion pair and the qualitative ion pair with compounds in the standard solution to obtain a characteristic peak of the to-be-detected organic phase; and obtaining the content of each compound in the sample to be detected according to the peak area of the characteristic peak of each compound and the quantitative standard curve equation.

The utility model discloses an automatic installation mechanism of automobile parts screw, including frame, the top of frame is connected with the frame and is equipped with X axis servo screw rod linear module, and the X axis of X axis servo screw rod linear module moves the slide table and is connected with Z axis servo screw rod linear module, and the Z axis of Z axis servo screw rod linear module moves the slide table and is connected with the electric wrench, and the electric wrench bottom is installed with the electric wrench head, and the screw locking head is fixed in the electric wrench head through the fixed component, and the fixed component is constituted by arc clamping block and spring, when needing to replace screw locking head, only need to exert certain external force to overcome the spring elasticity, make arc clamping block separate from the clamping slot of screw locking head, can conveniently and quickly dismantle the original locking head down, and install the new locking head of adapting different types screw, greatly improved the flexibility and versatility of mechanism in a variety of installation tasks, no longer stop because of screw type mismatch, ensure the continuity of production.

The application discloses a long spiral drilling machine concrete automatic pouring control method and system, the method comprises the following steps: in response to the pipeline filling rate and / or the concrete pressure reaching the preset value, the drill pipe automatic lifting mode is started; according to the feedforward speed and the feedback correction amount generated based on the concrete pressure deviation, the lifting speed is calculated, the winch equipment is controlled to lift the drill pipe according to the lifting speed, and the real-time correction of the lifting speed is carried out in the lifting process; the total lifting length is divided into multiple preset lengths, when the drill pipe is lifted by the preset length each time, the pile filling rate in the preset length range is calculated, if the pile filling rate is lower than the preset filling rate, the underfilling backfilling is carried out, after the backfilling is completed, the drill pipe returns to the original position and continues to lift until the concrete pouring is completed. The pouring process of the concrete is changed from the experience type manual adjustment to the closed loop control based on the pile filling rate and / or the concrete pressure, the underfilling and overfilling phenomena are avoided, and the piling quality is higher and more stable.

The invention discloses a venous transfusion intelligent speed regulation anti-leakage device and a working control method thereof, and the device comprises a speed regulation module, an anti-leakage monitoring module, a pressure protection module, a control module and an interaction module. Accurate adjustment of infusion flow speed, real-time monitoring and early warning of leakage and dynamic control of infusion pressure are achieved. The speed regulation module covers mechanical precise speed regulation and intelligent closed-loop speed control and adapts to multi-scene infusion requirements; the anti-leakage monitoring module realizes rapid identification and alarm of leakage through a conductivity sensing, pressure sensing or infrared imaging technology; and the pressure protection module avoids the risk of high-pressure leakage through a pressure release valve or pressure self-adaptive adjustment. The device is adaptive to traditional infusion equipment, is simple and convenient to operate, is controllable in cost, can remarkably improve the infusion safety and accuracy, reduces the nursing workload, and is suitable for the scenes of conventional infusion, special precise infusion and the like of medical institutions at all levels.

The invention discloses a laser scribing method, system and related device for reducing physical stress damage to a chip, and the method comprises the steps: obtaining the basic data of a to-be-scribed chip, and building a laser scribing database according to the basic data; collecting a feature image of the chip subjected to physical stress damage, and storing the feature image as initial data in the database as a first data feature; based on the current production plan, determining the type of a to-be-scribed chip, obtaining the information of the determined type of the to-be-scribed chip, and taking the information as a second data feature; and comparing the first data feature with the second data feature before performing scribing operation on the chip to obtain a data distinguishing point, and formulating a scribing operation mode according to the data distinguishing point. Through data comparison and analysis, risk points possibly causing physical stress damage can be identified in advance, so that the physical stress damage of the chip in the scribing process is effectively reduced.

This invention discloses an automatic product loading device, belonging to the technical field of loading devices. Its key features include: a six-axis industrial robot, a blank material bin, multiple machining centers equipped with dual-station fixtures, a discharge conveyor belt, and a safety fence; it also includes a reversing mechanism and a robot control integrated system, with the reversing mechanism corresponding to each machining center; the robot control integrated system includes a PLC controller capable of communicating with each machining center, the six-axis industrial robot connected to the PLC controller, responding to the machining center's call signals, and performing operations such as material picking, loading and unloading at the first station, sending workpieces to the reversing mechanism for reversal, loading at the second station, and sending finished products to the discharge conveyor belt; this invention can achieve fully automatic loading and unloading, reduce labor costs, and improve production stability and quality consistency.

The utility model relates to the technical field of control cabinets, and discloses a control cabinet of a reinjection water integrated system, which comprises a cabinet body front inner door and an overground display provided with a multifunctional human-computer interface and a UCS direct-reading sensor. A main power circuit breaker, a reinjection frequency converter, an electric quantity acquisition module, a vector frequency converter, a main output contactor, an anti-reversal contactor and a reinjection pump output contactor are arranged at the front part of the cabinet body; a control transformer, a power supply filter, a GPRS module, a temperature controller and an external signal terminal are arranged in the rear door of the cabinet body, and the multifunctional human-computer interface is connected with the reinjection frequency converter, the vector frequency converter, the electric quantity acquisition module and the UCS direct-reading sensor ground display through a 485 serial port communication network. According to the integrated control system for the screw pump and the reinjection pump, integrated control over the screw pump and the reinjection pump is achieved, meanwhile, the UCS direct-reading sensor, the ground displayer, the underground pressure sensor and the 485 communication network containing the GPRS module are matched, integrated collection of data is achieved, relevant operation data are uploaded in real time, and the data integration capacity is improved.

The invention provides an intelligent photovoltaic power station fault diagnosis system, which belongs to the technical field of photovoltaic power generation and comprises a data acquisition module for acquiring key component operation parameters, a quantum processing module for integrating the parameters, a pulse neural network module for performing secondary integration analysis on an integration result to determine a pulse output quantity, and a fault diagnosis module for performing fault diagnosis on the pulse output quantity. The fault diagnosis module decomposes the pulse output quantity to determine a fault state and analyzes the fault state with a diagnosis state to obtain a diagnosis result, and the visual interaction module displays the operation state and the diagnosis result; by adopting the quantum sensor, the pulse neural network and the quantum machine learning algorithm, the measurement precision, the data processing and analysis capability and the fault diagnosis accuracy and reliability can be improved, the existing technical problems are solved, and the stable operation of the photovoltaic power station is ensured.

This invention provides a high-efficiency, low-temperature-rise passive harmonic filter, belonging to the field of filters. It includes a main base housing and a top housing with evenly spaced heat dissipation side slots on both sides, which work in conjunction with symmetrically fixed cooling fans on the inner side to form an effective airflow channel. The cooling fans draw external cool air into the top housing, accelerating airflow and allowing heat to be quickly dissipated to the external environment, significantly improving heat dissipation efficiency. The evenly fixed heat dissipation side plates on the outer side of the passive harmonic filter further increase the heat dissipation area, while the porous structure of the perforated support plate also facilitates airflow and enhances the heat dissipation effect. Through these heat dissipation designs, the temperature rise of the filter during operation is effectively reduced, ensuring that the internal electronic components operate in a suitable temperature environment, improving component performance and lifespan, reducing the failure rate caused by overheating, and improving the reliability and stability of the filter.

The invention discloses a fuzzy adaptive sliding mode control method and system suitable for a satellite flexible solar wing system, and belongs to the technical field of spacecraft control. Aiming at the nonlinear vibration problem caused by structural flexibility, joint gaps and abrasion of a satellite flexible solar wing and the defects of poor trajectory tracking precision and the like caused by insufficient robustness, obvious buffeting and insufficient adaptive capacity of an existing control method, the method comprises the following steps of: constructing a nonlinear dynamic model for accurately representing complex dynamic characteristics of a system; and designing a fuzzy adaptive sliding mode control method to realize high-precision control of the attitude of the flexible solar wing. The method has the strong robustness of sliding mode control and the dynamic adaptation capability of fuzzy self-adaption, the inherent defects of a traditional control method are effectively overcome, the system operation stability and control precision are improved, and technical support is provided for reliable control of spacecraft flexible components.

The invention relates to a single molecule scanning, capturing and detecting control method, and belongs to the field of measurement and analysis. According to the method, a nanoscale glass microtube approaches the surface of a sample, and the distance between a probe and the sample is controlled by monitoring the current change in real time. The method comprises the following specific steps: preparation work, initialization of a nano control platform, approaching of a probe to a sample liquid level, approaching of the probe to a sample surface (coarse probe insertion), and approaching of the probe to the sample surface (fine probe insertion). The method can realize rapid capture of a single molecule and accurate detection of via hole current, realizes rapid scanning of sample molecule plane distribution and structure, can longitudinally capture and control a single long-chain molecule, feeds back blocking current of the long-chain molecule in a glass nanopore in real time, realizes structural feature detection of the single long-chain molecule, and has a good application prospect. The detection method can be used for detection of long-chain DNA and RNA molecules. The method has the advantages of simplicity in operation, high detection precision and the like, and has a wide application prospect in the fields of biomolecule detection, single molecule research and the like.

The present invention relates to the field of information processing, and in particular to an underwater acoustic spectrum segmentation communication method based on deep learning. A deep learning-based underwater acoustic spectrum segmentation communication method comprises: acquiring an underwater acoustic signal; generating an underwater acoustic spectrum graph through Mel-frequency cepstrum coefficients of the underwater acoustic signal; sending the underwater acoustic spectrum graph into an underwater acoustic spectrum segmentation model for processing to obtain an underwater acoustic spectrum annotation graph; mapping the available spectrum area in the underwater acoustic spectrum annotation graph to the underwater acoustic signal frequency band; and allocating all the underwater acoustic signal frequency bands to different network channels for transmission. The present invention converts the underwater acoustic signal into an underwater acoustic spectrum graph, and sends the underwater acoustic spectrum graph into an underwater acoustic spectrum segmentation model for processing. The underwater acoustic spectrum segmentation model adopts deep learning technology, and can segment and mark the available spectrum in the underwater acoustic spectrum graph based on the feature information in the underwater acoustic spectrum graph, thereby realizing the extraction and segmentation of the available frequency bands in the underwater acoustic signal.

The invention discloses a geothermal well internal foreign matter rapid identification and salvage control system, and relates to the technical field of geothermal well internal foreign matter identification and salvage control. Comprising an initial identification and positioning module, a real-time data acquisition module, a data analysis and flow prediction module, a flow state classification module, a stable flow identification module and a dynamic flow optimization module. And the initial recognition and positioning module is used for deploying a high-resolution camera in the geothermal well and carrying out initial foreign matter recognition and positioning operation according to the set initial exposure time. The high-resolution camera and the built-in measurement module are used for collecting hot water flow data in real time, the exposure time is dynamically adjusted in combination with a machine learning model, high-precision recognition under static flow is achieved, the exposure time is shortened under dynamic fluctuation so as to reduce motion blur, the recognition accuracy and efficiency are effectively improved, the missing detection risk is reduced, and the recognition efficiency is improved. And the response speed and parameter setting of the camera are optimized, so that the camera can flexibly cope with complex environment changes.

The utility model discloses an automatic product detection device based on visual identification, including frame, the detection cabin of being located on frame, conveying belt, defective product recycling system and control system, the inside detection chamber of detection cabin is equipped with and connects the visual identification system of control system, the top of detection cabin has seted up and installed the window, be equipped with the detection station of corresponding visual identification system on the conveying belt, the conveying belt runs through detection cabin, photoelectric trigger sensor is provided with to the conveying belt at detection station. Whole process does not need manual intervention, from product delivery, photoelectric trigger detection, to image acquisition, analysis determination and defective product recycling are all automatic completion, effectively solve the problem that traditional manual detection is low, subjective, easy to fatigue, adapt to large -scale production line continuous detection demand, and the overall rhythm efficiency is greatly promoted.

The present invention relates to the field of target simulation adjustment technology, and in particular to a target simulation system for realizing semi-physical simulation of an electric shovel. The system includes an electric shovel semi-physical simulation platform construction module, an electric shovel target operation pre-setting execution module, an electric shovel target operation parameter real-time acquisition module, and a target simulation feedback adjustment control optimization module. The electric shovel semi-physical simulation platform can be designed and established; the target operation parameter condition restrictions and electric shovel target operation execution processing are performed on the actual electric shovel structure to generate the electric shovel structure semi-physical target operation operation execution process, and the electric shovel operation parameters are collected in real time and uploaded to the electric shovel semi-physical physical simulation model; the electric shovel semi-physical physical simulation model is used to perform target simulation feedback error adjustment analysis and target execution control optimization to generate the electric shovel semi-physical target operation execution control optimization process. The present invention can realize the real simulation and dynamic adjustment of the electric shovel target operation process.

The invention provides a safety scheduling analysis method and system for black start of an electrochemical energy storage power station unit, and relates to the technical field of information, and the method comprises the steps: obtaining the real-time charge state data of each energy storage unit in an electrochemical energy storage power station; and carrying out noise removal and smoothing processing on the charge state data by adopting a Kalman filtering algorithm to obtain an accurate charge state estimation value. According to the invention, fault diagnosis and early warning are carried out through a support vector machine algorithm, the state of each unit is monitored in real time, and problem units are isolated timely. In the black start process, residual energy is continuously evaluated, a threshold value and a scheduling strategy are dynamically adjusted, safe and stable operation is ensured, after black start, the influence of the process on an energy storage unit is analyzed, a management strategy and parameter setting are optimized, and preparation is made for subsequent black start. According to the scheme, the black-start reliability and the energy utilization efficiency of the electrochemical energy storage power station are remarkably improved.